code: def prepare_config_and_inputs(self):
      input_ids_1 = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      )
      input_ids_2 = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      )
  
      lm_labels = None
      if self.use_labels:
          lm_labels = ids_tensor(
              [self.batch_size, self.seq_length], self.vocab_size
          )
  
      config = TransfoXLConfig(
          vocab_size=self.vocab_size,
          mem_len=self.mem_len,
          clamp_len=self.clamp_len,
          cutoffs=self.cutoffs,
          d_model=self.hidden_size,
          d_embed=self.d_embed,
          n_head=self.num_attention_heads,
          d_head=self.d_head,
          d_inner=self.d_inner,
          div_val=self.div_val,
          n_layer=self.num_hidden_layers,
          eos_token_id=self.eos_token_id,
          pad_token_id=self.vocab_size - 1,
          init_range=self.init_range,
          num_labels=self.num_labels,
      )
  
      return (config, input_ids_1, input_ids_2, lm_labels)
  
imports: import random
  import unittest
  from transformers import TransfoXLConfig, is_tf_available
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
label_desc: Use image node_id 2 for calling the TFTransfoXLModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids_1,  input_ids_2,  lm_labels